Challenges and Opportunities in SynthVaccine: The AI-Driven Revolution in Vaccine Design As of May 2025 Core Challenges Data Quality and Modeling Complexity Data Heterogeneity and Scarcity: SynthVaccine relies on integrating multi-omics data (genomics, epigenomics, proteomics), but inconsistent form … Challenges and Opportunities in SynthVaccine: The AI-Driven Revolution in Vaccine DesignRead more
CRISPR
Key Challenges and AI-Driven Solutions in RNA Therapeutics (RNAThera)
Key Challenges and AI-Driven Solutions in RNA Therapeutics (RNAThera) RNA therapeutics (RNAThera) face significant challenges in data complexity, target identification, delivery efficiency, and personalized treatment optimization. While existing resources do not explicitly mention RNAThera, innovati … Key Challenges and AI-Driven Solutions in RNA Therapeutics (RNAThera)Read more
Core Applications and Breakthrough Cases of BioAIGenome (AutoGenome)
Core Applications and Breakthrough Cases of BioAIGenome (AutoGenome) BioAIGenome (inferred as AutoGenome, developed by institutions like Huawei Cloud) is an automated AI modeling tool designed for genomic data. It addresses challenges in traditional biomedical research—such as data complexity and hi … Core Applications and Breakthrough Cases of BioAIGenome (AutoGenome)Read more
BioAIPharma Applications and Case Studies: AI-Driven Transformation in Biopharmaceuticals
BioAIPharma Applications and Case Studies: AI-Driven Transformation in Biopharmaceuticals Artificial Intelligence (AI) is revolutionizing biopharmaceutical research and development (BioAIPharma), permeating every stage from target discovery to clinical trials, manufacturing, and precision medicine. … BioAIPharma Applications and Case Studies: AI-Driven Transformation in BiopharmaceuticalsRead more
Challenges and Future Directions of CRISPR Technology
Challenges and Future Directions of CRISPR Technology Despite CRISPR’s revolutionary potential in precision medicine and gene therapy, its large-scale clinical application faces multiple challenges. Below, we outline key technical bottlenecks and future directions, integrating current research … Challenges and Future Directions of CRISPR TechnologyRead more
CRISPRSingle and Systems-Level Multi-Omics Integration: Building a Closed-Loop System for Functional Genomics
CRISPRSingle and Systems-Level Multi-Omics Integration: Building a Closed-Loop System for Functional Genomics 1. Technical Framework and Core Logic CRISPRSingle refers to a technology integrating CRISPR gene editing at the single-cell level with multi-omics analysis. Its core objective is to establi … CRISPRSingle and Systems-Level Multi-Omics Integration: Building a Closed-Loop System for Functional GenomicsRead more
Genetic Technologies and Human Longevity: Breakthroughs, Ethical Challenges, and Future Visions
Genetic Technologies and Human Longevity: Breakthroughs, Ethical Challenges, and Future Visions 1. Core Mechanisms of Lifespan Extension via Genetic Technologies Precision Regulation of Aging-Related Genes Gene Repair: CRISPR-Cas9 tools correct progeria-causing mutations (e.g., LMNA) or inhibit pro- … Genetic Technologies and Human Longevity: Breakthroughs, Ethical Challenges, and Future VisionsRead more
Edit omics: Definition, Disciplinary Scope, and Future Applications
编辑组学：定义、学科范围和未来应用 定义和学科范围 Editomics 是“Edit”和“Omics”的合成词，代表了一个科学领域，专注于通过将基因编辑技术与多组学方法（基因组学、转录组学、蛋白质组学等）相结合来系统分析生物编辑事件。其研究范围包括： 基因组编辑组学：使用 CRISPR、碱基编辑等对基因组进行靶向修饰，以研究系统性的生物学影响。 RNA 编辑组学：研究 RNA 水平编辑事件（例如，ADAR 介导的 A-to-I 编辑）及其在疾病中的作用，例如 EDK 数据库中记录的异常 RNA 编辑-疾病关联。 表观遗传编辑组学：调节表观遗传标记（例如，DNA 甲基化、组蛋白修饰）以改变基因表 … Edit omics: Definition, Disciplinary Scope, and Future ApplicationsRead more